Dergiler / Namık Kemal Tıp Dergisi / 2015 / Cilt: 3 Sayı: 1

A new insulin sensitivity index derived from fat mass index and quantitative insulin sensitivity check index

Sayfa
26–36
Yayın Tarihi
2016-04-21
DOI
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Key words Obesity, childhood, insulin sensitivity index

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Objective: Obesity has recently become one of the most important health problems throughout the world.
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Temel Bulgular & Veri:Indices previously described or introduced in this study have been evaluated to choose one, which is capable of exhibiting significant distinctions between healthy children and those involved in the classes of childhood obesity.
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Sonuç & Katkı:Key words Obesity, childhood, insulin sensitivity index
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Obezite · çocukluk çağı · insulin sensitivite indeksi

Özet

Objective: Obesity has recently become one of the most important health problems throughout the world. This fact led to the controversies on the clinical use of insulin sensitivity indices. Indices previously described or introduced in this study have been evaluated to choose one, which is capable of exhibiting significant distinctions between healthy children and those involved in the classes of childhood obesity. Materials and Methods: A total of 179 girls; 81 morbidly obese(MO), 42 obese(O), 16 overweight(OW) and 40 normal(N) participated in the study. Groups were constituted based upon age- and sex-specific body mass index percentiles tabulated by World Health Organization. Homeostasis Model Assessment of Insulin Resistance(HOMA-IR), HOMA-IR/BMI, log HOMA-IR, fasting glucose/fasting insulin ratio(FGIR), quantitative insulin sensitivity check index(QUICKI), Raynaud, reciprocal insulin indices and also new indices HOMA-IR*BMI, HOMA-IR*fat mass index(FMI), QUICKI*BMI, QUICKI*FMI were calculated. The cut-offs 3.16 and 2.5 for HOMA-IR, 7 and 6 for FGIR, 0.357 and 0.328 for QUICKI were evaluated to estimate insulin resistance. Statistical analyses were performed with Predictive Analytics SoftWare(PASW) Statistics 18. Results and Conclusion: QUICKI*FMI was able to make a clear-cut separation between the groups. A new trilogy for cut-offs (HOMA>2.5, FGIR<7, QUICKI<0.328); each giving the similar results, has been suggested. Multifaceted character of QUICKI was also introduced. QUICKI was capable of discriminating MO from O when 0.328 cut-off was used, and O from OW when 0.357 cut-off was used. QUICKI*FMI index, a new one, was unique in detecting the advanced level of differences(p≤0.005) between N-OW, OW-O and O-MO groups during childhood obesity. Key words Obesity, childhood, insulin sensitivity index

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Bu Makaleye Atıf Yap

Donma, M., Donma, O., Topçu, B., Aydın, M., Tülübaş, F., Nalbantoğlu, B., Demirkol, M., Gürel, A. (2016). A new insulin sensitivity index derived from fat mass index and quantitative insulin sensitivity check index. Namık Kemal Tıp Dergisi, Cilt: 3 Sayı: 1, 26–36. https://ajindex.com/articles/972357

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Kaynakça (7)

  1. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999–2010. JAMA 2012; 307(5): 483–490. Childhood overweight and obesity. Available from: http://www.who.int/dietphysicalactivity/childhood/en/ {Last updated: 2014} Childhood obesity facts. Available from: http://www.cdc.gov/healthyyouth/obesity/facts.htm/201 2 {Last updated: July 10, 2013} National Center for Health Statistics. Health, United States, 2011: With Special Features on Socioeconomic Status and Health. Hyattsville, MD; U.S. Department of Health and Human Services; 2012.
  2. Brufani C, Grossi A, Fintini D et al. Cardiovascular fitness, insulin resistance and metabolic syndrome in severely obese prepubertal Italian children. Horm Res 2008; 70(6): 349-356.
  3. Rizzo AC, Goldberg TB, Silva CC, Kurokawa CS, Nunes HR, Corrente JE. Metabolic syndrome risk factors in overweight, obese, and extremely obese Brazilian adolescents. Nutr J 2013; 12: 19. Tobisch B, Blatniczky L, Barkai L. Cardiometabolic risk factors and insulin resistance in obese children and adolescents: relation to puberty. Pediatr Obes 2013 Nov 13. [Epub ahead of print] Adam TC, Tsao S, Page KA, Hu H, Hasson RE, Goran MI. Insulin sensitivity and brain reward activation in overweight Hispanic girls: a pilot study. Pediatr Obes 2013 Dec 20. [Epub ahead of print] Antuna-Puente B, Disse E, Rabasa-Lhoret R, Laville M, Capeau J, Bastard JP. How can we measure insulin sensitivity/resistance? Diabetes Metab 2011; 37(3): 179–188.
  4. Henderson M, Rabasa-Lhoret R, Bastard JP et al. Original article Measuring insulin sensitivity in youth: How do the different indices compare with the goldstandard method? Diabetes Metab 2011; 37(1): 72–78
  5. Borai A, Livingston C, Kaddam I, Ferns G. Selection of the appropriate method for the assessment of insulin resistance. BMC Med Res Methodol 2011;11:158. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28(7): 412–419.
  6. Katz A, Nambi SS, Mather K et al. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 2000; 85(7): 2402-2410.
  7. Rössner SM, Neovius M, Mattsson A, Marcus C, Norgren S. HOMA-IR and QUICKI: decide on a general standard instead of making further comparisons. Acta Pædiatr 2010; 99(